Computers & Industrial Engineering最新文献

{"title":"Reliability and optimal age-based replacement policy for consecutive 2-out-of-n:G system equipped with protection blocks","authors":"Serkan Eryilmaz","doi":"10.1016/j.cie.2025.111120","DOIUrl":"10.1016/j.cie.2025.111120","url":null,"abstract":"<div><div>This paper concerns the reliability evaluation and optimal age-based replacement policy for the linear consecutive 2-out-of-<span><math><mi>n</mi></math></span>:G system whose two consecutive components are protected by a block that has its own failure rate. Two alternative methods are proposed to compute the reliability of the system. The first method is based on direct probabilistic approach and uses the reliability of the ordinary consecutive 2-out-of-<span><math><mi>n</mi></math></span>:G system. The second method is based on the concept of survival signature. Closed form equations for the system reliability and the mean number of failed components within the system are obtained. The optimal age-based replacement policy is also defined and studied. Extensive numerical results are presented to illustrate the findings.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111120"},"PeriodicalIF":6.7,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An inter-subgroup compensation mechanism by Nash bargaining game for managing non-cooperative behavior in group decision making","authors":"Jie Yang ,&nbsp;Jian Wu ,&nbsp;Francisco Chiclana ,&nbsp;Mingshuo Cao ,&nbsp;Ronald R. Yager","doi":"10.1016/j.cie.2025.111114","DOIUrl":"10.1016/j.cie.2025.111114","url":null,"abstract":"<div><div>Non-cooperative behavior exhibited by DMs when they must make excessive interest compromises hinders the achievement of group consensus. This study develops an inter-subgroup compensation mechanism using the Nash bargaining game under the minimum cost consensus model (MCCM) framework to managing non-cooperative behavior. First, a cooperative acceptability index (CAI) based on compromise limit costs is proposed to objectively identify non-cooperative behavior. By quantifying the acceptable compromise limit costs, the CAI ensures that consensus adjustments remain within acceptable bounds. Then, an inter-subgroup compensation mechanism is designed using the Nash bargaining game from the perspective of Kaldor–Hicks improvement. This mechanism enables cooperative DMs to incentivize non-cooperative peers via resource transfers, achieving dual optimization by minimizing collective costs and ensuring individual acceptability. Finally, a community renewal application example and comparison analysis are provided to illustrate the efficacy of the proposed approach.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111114"},"PeriodicalIF":6.7,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordinating oncologist appointments with chemotherapy treatments under uncertainty","authors":"Ege Ozyuksel ,&nbsp;Serhat Gul ,&nbsp;Tonguç Ünlüyurt ,&nbsp;Batuhan Çelik","doi":"10.1016/j.cie.2025.111123","DOIUrl":"10.1016/j.cie.2025.111123","url":null,"abstract":"<div><div>Scheduling chemotherapy treatments in outpatient chemotherapy clinics (OCCs) presents significant challenges due to limited resources, uncertainty in infusion durations, and the need for coordinating with oncologist consultations. This study addresses these challenges through integrating oncologist consultation and chemotherapy scheduling by determining appointment times for a daily list of patients. A two-stage stochastic mixed-integer programming model is developed, considering stochastic factors such as infusion durations and the statuses of chemotherapy treatment approvals after consultations. In the first stage of the model, patients of each oncologist are organized in a sequence, and appointment times are set. In the second stage, patients are assigned to chairs and nurses using an optimal myopic policy. The objective function penalizes the expected weighted sum of the total working time of the OCC and the waiting times of patients. To represent the original scenario set by a reduced scenario set, a scenario reduction algorithm is employed. The algorithm, a Wasserstein Distance-Based Local Search Algorithm (WD-LSA), is tested using real data from a major academic oncology hospital in Turkey. The performance of the WD-LSA algorithm is demonstrated by comparing with CPLEX for smaller number of scenarios and with heuristic algorithms for larger number of scenarios. We find that the gap is quite small when compared with CPLEX solutions and the solutions are much better than the solutions found by the practical scheduling heuristics from the literature. The trade-off between patient waiting time and total working time is assessed. The dependency of the performance measures to the number of oncologists and nurses is investigated. Lastly, the value of stochastic solution is estimated.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111123"},"PeriodicalIF":6.7,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated optimization approach for crowdshipping leveraging smart lockers as decentralized urban transshipment hubs","authors":"Xin-Yu Zhuang ,&nbsp;I-Lin Wang ,&nbsp;Chia-Yen Lee","doi":"10.1016/j.cie.2025.111137","DOIUrl":"10.1016/j.cie.2025.111137","url":null,"abstract":"<div><div>Urban last-mile delivery systems face increasing challenges from rising e-commerce demand, frequent delivery failures, and sustainability concerns. This paper presents a novel integration of decentralized smart lockers into crowdshipping operations, uniquely leveraging their excess capacity as ad hoc transshipment points to improve delivery networks. Specifically, parcels are transferred via smart lockers by one or more crowdshippers, reducing trip detours and expanding geographical coverage. Unlike prior studies, our approach eliminates the need for time-synchronized parcel handovers, significantly enhancing operational flexibility. A mixed-integer programming (MIP) model is developed to optimize driver-parcel assignments and routing for the entire system without imposing a single-transshipment assumption. However, to address scalability challenges in large instances, we introduce a rolling-horizon framework and two tailored column-generation algorithms—complete (CCG) and greedy (GCG)—which assume at most one transshipment per parcel. In experiments with 900 drivers and 300 parcels, the CCG achieves exact solutions in 20 min under this assumption, while the GCG demonstrates a 12.1% cost reduction with a 1–2% optimality gap, requiring significantly less computation time. Although the MIP and rolling-horizon models can only solve smaller instances, they validate the effectiveness of the algorithms. This study provides practical and scalable solutions for overcoming last-mile delivery challenges.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111137"},"PeriodicalIF":6.7,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic task allocations with Q-learning based particle swarm optimization for human-robot collaboration disassembly of electric vehicle battery recycling","authors":"Jinhua Xiao ,&nbsp;Zhiwen Zhang ,&nbsp;Sergio Terzi ,&nbsp;Nabil Anwer ,&nbsp;Benoît Eynard","doi":"10.1016/j.cie.2025.111133","DOIUrl":"10.1016/j.cie.2025.111133","url":null,"abstract":"<div><div>With the wide application of Electric Vehicles (EV) and intelligent technology, the recycling of EV batteries presents significant challenges to cope with the dynamic disassembly tasks and operations. Similarly, human-robot collaborative (HRC) disassembly has emerged as an effective solution to accomplish the disassembly task allocation and improve efficiency. This paper proposed an improved HRC disassembly method integrating Q-learning-based Particle Swarm Optimization (PSO) to optimize the disassembly task sequence for multi-agent disassembly strategies. Furthermore, the Q-learning model is integrated to guide the variable neighborhood search (VNS) algorithm enabling efficient neighborhood structure selection to enhance local search capabilities and optimize multi-agent disassembly sorting tasks. By considering the disassembly experiment of Mercedes-Benz EQS NCM 811 battery as a case study, the proposed method is deeply analyzed and compared with traditional methods under the same objective function. The results demonstrate the proposed algorithm reduces the fitness value and improves the optimization of disassembly tasks. The experimental results show that the proposed algorithm effectively improves the efficiency of HRC disassembly compared to other algorithms, offering a more efficient solution for the recycling of retired EV batteries.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111133"},"PeriodicalIF":6.7,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143858938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Considering regret psychology and non-cooperative competition among alternatives for heterogeneous multi-attribute group decision making","authors":"Yang Huang ,&nbsp;Meiqiang Wang","doi":"10.1016/j.cie.2025.111132","DOIUrl":"10.1016/j.cie.2025.111132","url":null,"abstract":"<div><div>In reality, to select the best one from a set of alternatives, there are widespread situations that require several experts to assess the attribute values of each alternative with heterogeneous information. The purpose of this paper is to solve the heterogeneous multi-attribute group decision making (HMAGDM) problems with attribute values involving real numbers, intervals, intuitionistic fuzzy sets, interval type-2 fuzzy sets, and interval-valued hesitant fuzzy sets from the perspective that alternatives have regret psychology with respect to the assessment information and that there is a non-cooperative competitive relationship among alternatives. Therefore, a method based on regret theory and interval data envelopment analysis (DEA) game cross-efficiency model is proposed for HMAGDM. The method adopts a process of aggregation followed by exploration. In the aggregation phase, a regret theory-based expert weight determination model is constructed to derive the weights of experts, and the individual decision matrices provided by individual experts are further aggregated into a collective decision matrix. Then, the heterogeneous information in the collective decision matrix is uniformly converted into intervals, which are represented as variables with unknown parameters. According to these variables, a regret theory-based interval DEA game cross-efficiency model is proposed to calculate the comprehensive values of alternatives and thus rank alternatives. The feasibility and effectiveness of the proposed method are illustrated by a supplier selection example.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111132"},"PeriodicalIF":6.7,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143854916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating machine learning based EWMA control charts for multivariate process monitoring","authors":"Muhammad Waqas Kazmi,&nbsp;Muhammad Noor-ul-Amin","doi":"10.1016/j.cie.2025.111131","DOIUrl":"10.1016/j.cie.2025.111131","url":null,"abstract":"<div><div>Memory-type control charts, such as the multivariate EWMA (MEWMA), are recognized for their effectiveness in detecting small to moderate changes in the process mean vector. In comparison, Adaptive Multivariate EWMA (AMEWMA) control charts offer superior capabilities over traditional methods. This study proposes an adaptive multivariate EWMA (SAMEWMA) control chart based on Machine Learning (ML) techniques such as Random Forest (RF), K-NN, and Support Vector Regression (SVR) to monitor specifically small shifts in the process mean vector. The results show that the proposed chart demonstrates exceptional performance in detecting small shifts in the mean vector compared to various existing charts, such as AMEWMA-I and AMEWMA-II. Investigations also prove the superiority of the SVR method among other ML approaches. The Average Run Length (ARL) matric is employed to determine the performance of the control charts using the Monte Carlo (MC) simulation technique. Two real-world examples are presented to demonstrate the effectiveness and superiority of the proposed control chart in detecting variations in the process mean vector.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111131"},"PeriodicalIF":6.7,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluating machine learning-driven intrusion detection systems in IoT: Performance and energy consumption","authors":"Saeid Jamshidi ,&nbsp;Kawser Wazed Nafi ,&nbsp;Amin Nikanjam ,&nbsp;Foutse Khomh","doi":"10.1016/j.cie.2025.111103","DOIUrl":"10.1016/j.cie.2025.111103","url":null,"abstract":"<div><div>In the landscape of network security, the integration of Machine Learning (ML)-based Intrusion Detection System (IDS) represents a significant leap forward, especially in the domain of the Internet of Things (IoT) and Software-Defined Networking (SDN). Such ML-based IDS are crucial for improving security infrastructures, and their importance is increasingly pronounced in IoT systems. However, despite the rapid advancement of ML-based IDS, there remains a gap in understanding their impact on critical performance metrics (e.g., CPU load, energy consumption, and CPU usage) in resource-constrained IoT devices. This becomes especially crucial in scenarios involving real-time cyber threats that challenge IoT devices in a public/private network.</div><div>To address this gap, this article presents an empirical study that evaluates the impact of state-of-the-art ML-based IDSs on performance metrics such as CPU usage, energy consumption, and CPU load in the absence and presence of real-time cyber threats, with a specific focus on their deployment at the edge of IoT infrastructures. We also incorporate SDN to evaluate the comparative performance of ML-based IDSs with and without SDN. To do so, we focus on the impact of both SDN’s centralized control and dynamic resource management on the performance metrics of an IoT system. Finally, we analyze our findings using statistical analysis using the Analysis of Variance (ANOVA) analysis. Our findings demonstrate that traditional ML-based IDS, when implemented at the edge gateway with and without SDN architecture, significantly affects performance metrics against cyber threats compared to DL-based ones. Also, we observed substantial increases in energy consumption, CPU usage, and CPU load during real-time cyber threat scenarios at the edge, underscoring the resource-intensive nature of these systems. This research fills the existing knowledge void and delivers essential insights into the operational dynamics of ML-based IDS at edge gateway in IoT systems.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111103"},"PeriodicalIF":6.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trust driven group decision making: Research progress and prospects from the perspective of consensus","authors":"Mingshuo Cao ,&nbsp;Qi Sun ,&nbsp;Francisco Chiclana ,&nbsp;Yujia Liu ,&nbsp;Tiantian Gai ,&nbsp;Yiling Yang ,&nbsp;Jian Wu","doi":"10.1016/j.cie.2025.111101","DOIUrl":"10.1016/j.cie.2025.111101","url":null,"abstract":"<div><div>Trust driven Group Decision Making (TGDM) is a new type of decision making process conducted through trust relationships and information exchange between individuals in the social network environment. By systematically organizing the research progress of TGDM and exploring its future research directions, the GDM research for consensus will be promoted. Firstly, this article combs the development status and research trends in recent years based on bibliometrics methods, and then summarizes and discusses the important literature related to TGDM. Secondly, it defines the scientific research category and basic framework of GDM and TGDM. Thirdly, the basic related concepts of TGDM problems are summarized, and then its characteristics and function are analyzed. Finally, it analyzes the problems and challenges faced by TGDM research and explores future research directions. It finds that many scholars have constructed multi-dimensional TGDM models from different perspectives, which have shown wonderful application performance in fields such as product design, failure mode and effects analysis, meta universe virtual communities, and Water–Energy–Food. In addition, it will be a very promising research direction to in-depth investigate TGDM driven by scene, behavior and decision maker’s personality characteristics.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111101"},"PeriodicalIF":6.7,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A data-driven modelling framework for predicting the quality of semiconductor devices to support burn-in decisions","authors":"Ibrahim Ahmed ,&nbsp;Piero Baraldi ,&nbsp;Enrico Zio ,&nbsp;Horst Lewitschnig","doi":"10.1016/j.cie.2025.111115","DOIUrl":"10.1016/j.cie.2025.111115","url":null,"abstract":"<div><div>Burn-in testing of semiconductor devices is performed to ensure product quality by identifying and removing early-life failures. Given the cost and time required by burn-in testing, this work proposes a framework to predict the quality of a production batch of semiconductor devices before burn-in. Unlike traditional methods for quality prediction that rely solely on statistical data, this framework incorporates production data to improve prediction accuracy. The framework combines statistical methods for feature extraction (Piecewise Aggregate Approximation and Principal Component Analysis) and quality estimation (Clopper-Pearson Estimator) with a modified Probabilistic Support Vector Regression (PSVR) to predict early-life failures. The PSVR hyperparameters are set by a Bayesian Optimization (BO) technique. The framework is validated on a synthetic case study designed to emulate the BI process of semiconductor devices and, then, applied to real data collected during semiconductor production. Results from a synthetic case study and real-world semiconductor production data demonstrate the accuracy of the proposed method in predicting the quality of production batches. The quality predictions can, then, be used to inform efficient burn-in test planning in terms of the number of devices to undergo burn-in and the type of burn-in tests to perform.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"204 ","pages":"Article 111115"},"PeriodicalIF":6.7,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143829998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}